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@inproceedings{818315,
author = {Večeřa, Martin and Popelínský, Lubomír},
address = {Praha},
booktitle = {Late Breaking Papers, Inductive Logic Programming, 18th International Conference},
keywords = {spatio-temporal data; multi-relational data mining; frequent pat- terns; association rules},
language = {eng},
location = {Praha},
isbn = {978-80-86742-26-7},
pages = {117-122},
publisher = {FEL ČVUT},
title = {Relational Data Mining in Crisis Management},
url = {http://www.fi.muni.cz/kd},
year = {2008}
}
TY - JOUR
ID - 818315
AU - Večeřa, Martin - Popelínský, Lubomír
PY - 2008
TI - Relational Data Mining in Crisis Management
PB - FEL ČVUT
CY - Praha
SN - 9788086742267
KW - spatio-temporal data
KW - multi-relational data mining
KW - frequent pat- terns
KW - association rules
UR - http://www.fi.muni.cz/kd
L2 - http://www.fi.muni.cz/kd
N2 - We propose an extension of current ILP systems to support spatio-temporal data mining in crisis management. A new framework is presented based on PostGIS and the multi-relational learner GRAPE. Data on floods in the Czech Republic will be used for testing.
ER -
VEČEŘA, Martin a Lubomír POPELÍNSKÝ. Relational Data Mining in Crisis Management. In \textit{Late Breaking Papers, Inductive Logic Programming, 18th International Conference}. Praha: FEL ČVUT, 2008, s.~117-122. ISBN~978-80-86742-26-7.
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